Virtual network health checker

ABSTRACT

Systems, methods, and computer-readable storage media are provided for managing status of state machines in a computing network. Various embodiments of the present technology can be used to track and maintain an active log associated with each state machine in a computing network. The active log of a state machine can be periodically analyzed at a predetermined time interval to determine an anticipated state of the state machine and a current state of the state machine. In response to determining that the state machine is in an inconsistent state (i.e., the anticipated state does not match the current state of the state machine), a suitable action can be taken to switch the current state of the state machine from the inconsistent state to a suitable new state.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to U.S. Provisional Application No.62/167,787, filed May 28, 2015, the disclosure of which is incorporatedherein by reference in its entirety.

TECHNICAL FIELD

The present technology relates in general to the field of computernetworks, and more specifically to methods and systems for managing astate machine.

BACKGROUND

Modern computing networks operate with an increasing number of computingnodes to support a wide variety of applications and services. Computingnodes in the networks may include a switch (e.g., a router) or an endpoint (e.g., a host device). A computing node can be a state machine andoperate on an input to change the status and/or cause an action to takeplace for a given change.

However, it's a challenge to ensure that a state machine is not in aninconsistent state or does not remain in an inconsistent state for anextended period of time. This problem becomes even more challenging whencomplexities of state machines increase beyond moderate levels and canbe exposed to corner cases and race conditions.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features of the disclosure can be obtained, a moreparticular description of the principles briefly described above will berendered by reference to specific examples thereof which are illustratedin the appended drawings. Understanding that these drawings depict onlyexamples of the disclosure and are not therefore to be considered to belimiting of its scope, the principles herein are described and explainedwith additional specificity and detail through the use of theaccompanying drawings in which:

FIG. 1 illustrates an example network device according to some aspectsof the subject technology;

FIGS. 2A and 2B illustrate an example system embodiment according tosome aspects of the subject technology;

FIG. 3 illustrates a schematic block diagram of an example architecturefor a network fabric;

FIG. 4 illustrates an example overlay network;

FIG. 5 illustrates an example health checker for managing a statemachine according to some aspects of the subject technology; and

FIG. 6 illustrates an example process of managing statuses of a statemachine in a computing network.

DESCRIPTION OF EXAMPLE EMBODIMENTS

The detailed description set forth below is intended as a description ofvarious configurations of the subject technology and is not intended torepresent the only configurations in which the subject technology can bepracticed. The appended drawings are incorporated herein and constitutea part of the detailed description. The detailed description includesspecific details for the purpose of providing a more thoroughunderstanding of the subject technology. However, it will be clear andapparent that the subject technology is not limited to the specificdetails set forth herein and may be practiced without these details. Insome instances, structures and components are shown in block diagramform in order to avoid obscuring the concepts of the subject technology.

Overview:

Disclosed are systems, methods, and computer-readable storage media formanaging states of state machines in a computing network. Variousembodiments of the present technology can be used to track and maintainan active log associated with each state machine in a computing network.The active log of a state machine can be periodically analyzed at apredetermined time interval to determine an anticipated state of thestate machine and a current state of the state machine. In response todetermining that the state machine is in an inconsistent state (i.e.,the anticipated state does not match the current state of the statemachine), a suitable action can be taken to switch the current state ofthe state machine from the inconsistent state to a suitable new state.

DETAILED DESCRIPTION

A computer network is a geographically distributed collection of nodesinterconnected by communication links and segments for transporting databetween endpoints, such as personal computers and workstations. Manytypes of networks are available, with the types ranging from local areanetworks (LANs) and wide area networks (WANs) to overlay andsoftware-defined networks, such as virtual extensible local areanetworks (VXLANs).

LANs typically connect nodes over dedicated private communications linkslocated in the same general physical location, such as a building orcampus. WANs, on the other hand, typically connect geographicallydispersed nodes over long-distance communications links, such as commoncarrier telephone lines, optical lightpaths, synchronous opticalnetworks (SONET), or synchronous digital hierarchy (SDH) links. LANs andWANs can include layer 2 (L2) and/or layer 3 (L3) networks and devices.

The Internet is an example of a WAN that connects disparate networksthroughout the world, providing global communication between nodes onvarious networks. The nodes typically communicate over the network byexchanging discrete frames or packets of data according to predefinedprotocols, such as the Transmission Control Protocol/Internet Protocol(TCP/IP). In this context, a protocol can refer to a set of rulesdefining how the nodes interact with each other. Computer networks maybe further interconnected by an intermediate network node, such as arouter, to extend the effective “size” of each network.

Overlay networks generally allow virtual networks to be created andlayered over a physical network infrastructure. Overlay networkprotocols, such as Virtual Extensible LAN (VXLAN), NetworkVirtualization using Generic Routing Encapsulation (NVGRE), NetworkVirtualization Overlays (NVO3), and Stateless Transport Tunneling (STT),provide a traffic encapsulation scheme which allows network traffic tobe carried across L2 and L3 networks over a logical tunnel. Such logicaltunnels can be originated and terminated through virtual tunnel endpoints (VTEPs).

Moreover, overlay networks can include virtual segments, such as VXLANsegments in a VXLAN overlay network, which can include virtual L2 and/orL3 overlay networks over which virtual machines (VMs) communicate. Thevirtual segments can be identified through a virtual network identifier(VNI), such as a VXLAN network identifier, which can specificallyidentify an associated virtual segment or domain.

Network virtualization allows hardware and software resources to becombined in a virtual network. For example, network virtualization canallow multiple numbers of VMs to be attached to the physical network viarespective virtual LANs (VLANs). The VMs can be grouped according totheir respective VLAN, and can communicate with other VMs as well asother devices on the internal or external network.

Network segments, such as physical or virtual segments; networks;devices; ports; physical or logical links; and/or traffic in general canbe grouped into a bridge or flood domain. A bridge domain or flooddomain can represent a broadcast domain, such as an L2 broadcast domain.A bridge domain or flood domain can include a single subnet, but canalso include multiple subnets. Moreover, a bridge domain can beassociated with a bridge domain interface on a network device, such as aswitch. A bridge domain interface can be a logical interface whichsupports traffic between an L2 bridged network and an L3 routed network.In addition, a bridge domain interface can support internet protocol(IP) termination, VPN termination, address resolution handling, MACaddressing, etc. Both bridge domains and bridge domain interfaces can beidentified by a same index or identifier.

Furthermore, endpoint groups (EPGs) can be used in a network for mappingapplications to the network. In particular, EPGs can use a grouping ofapplication endpoints in a network to apply connectivity and policy tothe group of applications. EPGs can act as a container for buckets orcollections of applications, or application components, and tiers forimplementing forwarding and policy logic. EPGs also allow separation ofnetwork policy, security, and forwarding from addressing by insteadusing logical application boundaries.

Cloud computing can also be provided in one or more networks to providecomputing services using shared resources. Cloud computing can generallyinclude Internet-based computing in which computing resources aredynamically provisioned and allocated to client or user computers orother devices on-demand, from a collection of resources available viathe network (e.g., “the cloud”). Cloud computing resources, for example,can include any type of resource, such as computing, storage, andnetwork devices, virtual machines (VMs), etc. For instance, resourcesmay include service devices (firewalls, deep packet inspectors, trafficmonitors, load balancers, etc.), compute/processing devices (servers,CPU's, memory, brute force processing capability), storage devices(e.g., network attached storages, storage area network devices), etc. Inaddition, such resources may be used to support virtual networks,virtual machines (VM), databases, applications (Apps), etc.

Cloud computing resources may include a “private cloud,” a “publiccloud,” and/or a “hybrid cloud.” A “hybrid cloud” can be a cloudinfrastructure composed of two or more clouds that inter-operate orfederate through technology. In essence, a hybrid cloud is aninteraction between private and public clouds where a private cloudjoins a public cloud and utilizes public cloud resources in a secure andscalable manner. Cloud computing resources can also be provisioned viavirtual networks in an overlay network, such as a VXLAN.

Disclosed are systems and methods for managing states of a state machinein a computing network. A brief introductory description of an exemplarysystems and networks, as illustrated in FIGS. 1 through 4, is disclosedherein. A detailed description of a health checker, and examplevariations, will then follow. These variations shall be described as thevarious embodiments are set forth. The disclosure now turns to FIG. 1.

FIG. 1 illustrates an exemplary network device 110 suitable forimplementing the present technology. Network device 110 includes amaster central processing unit (CPU) 162, interfaces 168, and a bus 115(e.g., a PCI bus). When acting under the control of appropriate softwareor firmware, the CPU 162 is responsible for executing packet management,error detection, and/or routing functions, such policy enforcement, forexample. The CPU 162 preferably accomplishes all these functions underthe control of software including an operating system and anyappropriate applications software. CPU 162 may include one or moreprocessors 163 such as a processor from the Motorola family ofmicroprocessors or the MIPS family of microprocessors. In an alternativeembodiment, processor 163 is specially designed hardware for controllingthe operations of router 110. In a specific embodiment, a memory 161(such as non-volatile RAM and/or ROM) also forms part of CPU 162.However, there are many different ways in which memory could be coupledto the system.

The interfaces 168 are typically provided as interface cards (sometimesreferred to as “line cards”). Generally, they control the sending andreceiving of data packets over the network and sometimes support otherperipherals used with the network device 110. Among the interfaces thatmay be provided are Ethernet interfaces, frame relay interfaces, cableinterfaces, DSL interfaces, token ring interfaces, and the like. Inaddition, various very high-speed interfaces may be provided such asfast token ring interfaces, wireless interfaces, Ethernet interfaces,Gigabit Ethernet interfaces, ATM interfaces, HSSI interfaces, POSinterfaces, FDDI interfaces and the like. Generally, these interfacesmay include ports appropriate for communication with the appropriatemedia. In some cases, they may also include an independent processorand, in some instances, volatile RAM. The independent processors maycontrol such communications intensive tasks as packet switching, mediacontrol, and management. By providing separate processors for thecommunications intensive tasks, these interfaces allow the mastermicroprocessor 162 to efficiently perform routing computations, networkdiagnostics, security functions, etc.

Although the system shown in FIG. 1 is one specific network device ofthe present technology, it is by no means the only network devicearchitecture on which the present technology can be implemented. Forexample, an architecture having a single processor that handlescommunications as well as routing computations, etc. is often used.Further, other types of interfaces and media could also be used with therouter.

Regardless of the network device's configuration, it may employ one ormore memories or memory modules (including memory 161) configured tostore program instructions for the general-purpose network operationsand mechanisms for roaming, route optimization and routing functionsdescribed herein. The program instructions may control the operation ofan operating system and/or one or more applications, for example. Thememory or memories may also be configured to store tables such asmobility binding, registration, and association tables, etc.

FIG. 2A, and FIG. 2B illustrate exemplary possible system embodiments.The more appropriate embodiment will be apparent to those of ordinaryskill in the art when practicing the present technology. Persons ofordinary skill in the art will also readily appreciate that other systemembodiments are possible.

FIG. 2A illustrates a conventional system bus computing systemarchitecture 200 wherein the components of the system are in electricalcommunication with each other using a bus 205. Exemplary system 200includes a processing unit (CPU or processor) 210 and a system bus 205that couples various system components including the system memory 215,such as read only memory (ROM) 220 and random access memory (RAM) 225,to the processor 210. The system 200 can include a cache of high-speedmemory connected directly with, in close proximity to, or integrated aspart of the processor 210. The system 200 can copy data from the memory215 and/or the storage device 230 to the cache 212 for quick access bythe processor 210. In this way, the cache can provide a performanceboost that avoids processor 210 delays while waiting for data. These andother modules can control or be configured to control the processor 210to perform various actions. Other system memory 215 may be available foruse as well. The memory 215 can include multiple different types ofmemory with different performance characteristics. The processor 210 caninclude any general purpose processor and a hardware module or softwaremodule, such as module 1 232, module 2 234, and module 3 236 stored instorage device 230, configured to control the processor 210 as well as aspecial-purpose processor where software instructions are incorporatedinto the actual processor design. The processor 210 may essentially be acompletely self-contained computing system, containing multiple cores orprocessors, a bus, memory controller, cache, etc. A multi-core processormay be symmetric or asymmetric.

To enable user interaction with the computing device 200, an inputdevice 245 can represent any number of input mechanisms, such as amicrophone for speech, a touch-sensitive screen for gesture or graphicalinput, keyboard, mouse, motion input, speech and so forth. An outputdevice 235 can also be one or more of a number of output mechanismsknown to those of skill in the art. In some instances, multimodalsystems can enable a user to provide multiple types of input tocommunicate with the computing device 200. The communications interface240 can generally govern and manage the user input and system output.There is no restriction on operating on any particular hardwarearrangement and therefore the basic features here may easily besubstituted for improved hardware or firmware arrangements as they aredeveloped.

Storage device 230 is a non-volatile memory and can be a hard disk orother types of computer readable media which can store data that areaccessible by a computer, such as magnetic cassettes, flash memorycards, solid state memory devices, digital versatile disks, cartridges,random access memories (RAMs) 225, read only memory (ROM) 220, andhybrids thereof.

The storage device 230 can include software modules 232, 234, 236 forcontrolling the processor 210. Other hardware or software modules arecontemplated. The storage device 230 can be connected to the system bus205. In one aspect, a hardware module that performs a particularfunction can include the software component stored in acomputer-readable medium in connection with the necessary hardwarecomponents, such as the processor 210, bus 205, display 235, and soforth, to carry out the function.

FIG. 2B illustrates a computer system 250 having a chipset architecturethat can be used in executing the described method and generating anddisplaying a graphical user interface (GUI). Computer system 250 is anexample of computer hardware, software, and firmware that can be used toimplement the disclosed technology. System 250 can include a processor255, representative of any number of physically and/or logicallydistinct resources capable of executing software, firmware, and hardwareconfigured to perform identified computations. Processor 255 cancommunicate with a chipset 260 that can control input to and output fromprocessor 255. In this example, chipset 260 outputs information tooutput 265, such as a display, and can read and write information tostorage device 270, which can include magnetic media, and solid statemedia, for example. Chipset 260 can also read data from and write datato RAM 275. A bridge 280 for interfacing with a variety of userinterface components 285 can be provided for interfacing with chipset260. Such user interface components 285 can include a keyboard, amicrophone, touch detection and processing circuitry, a pointing device,such as a mouse, and so on. In general, inputs to system 250 can comefrom any of a variety of sources, machine generated and/or humangenerated.

Chipset 260 can also interface with one or more communication interfaces290 that can have different physical interfaces. Such communicationinterfaces can include interfaces for wired and wireless local areanetworks, for broadband wireless networks, as well as personal areanetworks. Some applications of the methods for generating, displaying,and using the GUI disclosed herein can include receiving ordereddatasets over the physical interface or be generated by the machineitself by processor 255 analyzing data stored in storage 270 or 275.Further, the machine can receive inputs from a user via user interfacecomponents 285 and execute appropriate functions, such as browsingfunctions by interpreting these inputs using processor 255.

It can be appreciated that exemplary systems 200 and 250 can have morethan one processor 210 or be part of a group or cluster of computingdevices networked together to provide greater processing capability.

FIG. 3 illustrates a schematic block diagram of an example architecture300 for a network fabric 312. The network fabric 312 can include spineswitches 302 _(A), 302 _(B), . . . , 302 _(N) (collectively “302”)connected to leaf switches 304 _(A), 304 _(B), 304 _(C) . . . 304 _(N)(collectively “304”) in the network fabric 312.

Spine switches 302 can be L3 switches in the fabric 312. However, insome cases, the spine switches 302 can also, or otherwise, perform L2functionalities. Further, the spine switches 302 can support variouscapabilities, such as 40 or 10 Gbps Ethernet speeds. To this end, thespine switches 302 can include one or more 40 Gigabit Ethernet ports.Each port can also be split to support other speeds. For example, a 40Gigabit Ethernet port can be split into four 10 Gigabit Ethernet ports.

In some embodiments, one or more of the spine switches 302 can beconfigured to host a proxy function that performs a lookup of theendpoint address identifier to locator mapping in a mapping database onbehalf of leaf switches 304 that do not have such mapping. The proxyfunction can do this by parsing through the packet to the encapsulated,tenant packet to get to the destination locator address of the tenant.The spine switches 302 can then perform a lookup of their local mappingdatabase to determine the correct locator address of the packet andforward the packet to the locator address without changing certainfields in the header of the packet.

When a packet is received at a spine switch 302 _(i), the spine switch302 _(i) can first check if the destination locator address is a proxyaddress. If so, the spine switch 302 _(i) can perform the proxy functionas previously mentioned. If not, the spine switch 302 _(i) can look upthe locator in its forwarding table and forward the packet accordingly.

Spine switches 302 connect to leaf switches 304 in the fabric 312. Leafswitches 304 can include access ports (or non-fabric ports) and fabricports. Fabric ports can provide uplinks to the spine switches 302, whileaccess ports can provide connectivity for devices, hosts, endpoints,VMs, or external networks to the fabric 312.

Leaf switches 304 can reside at the edge of the fabric 312, and can thusrepresent the physical network edge. In some cases, the leaf switches304 can be top-of-rack (“ToR”) switches configured according to a ToRarchitecture. In other cases, the leaf switches 304 can be aggregationswitches in any particular topology, such as end-of-row (EoR) ormiddle-of-row (MoR) topologies. The leaf switches 304 can also representaggregation switches, for example.

The leaf switches 304 can be responsible for routing and/or bridging thetenant packets and applying network policies. In some cases, a leafswitch can perform one or more additional functions, such asimplementing a mapping cache, sending packets to the proxy function whenthere is a miss in the cache, encapsulate packets, enforce ingress oregress policies, etc.

Moreover, the leaf switches 304 can contain virtual switchingfunctionalities, such as a virtual tunnel endpoint (VTEP) function asexplained below in the discussion of VTEP 408 in FIG. 4. To this end,leaf switches 304 can connect the fabric 312 to an overlay network, suchas overlay network 400 illustrated in FIG. 4.

Network connectivity in the fabric 312 can flow through the leafswitches 304. Here, the leaf switches 304 can provide servers,resources, endpoints, external networks, or VMs access to the fabric312, and can connect the leaf switches 304 to each other. In some cases,the leaf switches 304 can connect EPGs to the fabric 312 and/or anyexternal networks. Each EPG can connect to the fabric 312 via one of theleaf switches 304, for example.

Endpoints 310A-E (collectively “310”) can connect to the fabric 312 vialeaf switches 304. For example, endpoints 310A and 310B can connectdirectly to leaf switch 304A, which can connect endpoints 310A and 310Bto the fabric 312 and/or any other one of the leaf switches 304.Similarly, endpoint 310E can connect directly to leaf switch 304C, whichcan connect endpoint 310E to the fabric 312 and/or any other of the leafswitches 304. On the other hand, endpoints 310C and 310D can connect toleaf switch 304B via L2 network 306. Similarly, the wide area network(WAN) can connect to the leaf switches 304C or 304D via L3 network 308.

Endpoints 310 can include any communication device, such as a computer,a server, a switch, a router, etc. In some cases, the endpoints 310 caninclude a server, hypervisor, or switch configured with a VTEPfunctionality which connects an overlay network, such as overlay network400 below, with the fabric 312. For example, in some cases, theendpoints 310 can represent one or more of the VTEPs 408A-D illustratedin FIG. 4. Here, the VTEPs 408A-D can connect to the fabric 312 via theleaf switches 304. The overlay network can host physical devices, suchas servers, applications, EPGs, virtual segments, virtual workloads,etc. In addition, the endpoints 310 can host virtual workload(s),clusters, and applications or services, which can connect with thefabric 312 or any other device or network, including an externalnetwork. For example, one or more endpoints 310 can host, or connect to,a cluster of load balancers or an EPG of various applications.

Although the fabric 312 is illustrated and described herein as anexample leaf-spine architecture, one of ordinary skill in the art willreadily recognize that the subject technology can be implemented basedon any network fabric, including any data center or cloud networkfabric. Indeed, other architectures, designs, infrastructures, andvariations are contemplated herein.

FIG. 4 illustrates an exemplary overlay network 400. Overlay network 400uses an overlay protocol, such as VXLAN, VGRE, VO3, or STT, toencapsulate traffic in L2 and/or L3 packets which can cross overlay L3boundaries in the network. As illustrated in FIG. 4, overlay network 400can include hosts 406A-D interconnected via network 402.

Network 402 can include a packet network, such as an IP network, forexample. Moreover, network 402 can connect the overlay network 400 withthe fabric 312 in FIG. 3. For example, VTEPs 408A-D can connect with theleaf switches 304 in the fabric 312 via network 402.

Hosts 406A-D include virtual tunnel end points (VTEP) 408A-D, which canbe virtual nodes or switches configured to encapsulate andde-encapsulate data traffic according to a specific overlay protocol ofthe network 400, for the various virtual network identifiers (VNIDs)410A-I. Moreover, hosts 406A-D can include servers containing a VTEPfunctionality, hypervisors, and physical switches, such as L3 switches,configured with a VTEP functionality. For example, hosts 406A and 406Bcan be physical switches configured to run VTEPs 408A-B. Here, hosts406A and 406B can be connected to servers 404A-D, which, in some cases,can include virtual workloads through VMs loaded on the servers, forexample.

In some embodiments, network 400 can be a VXLAN network, and VTEPs408A-D can be VXLAN tunnel end points (VTEP). However, as one ofordinary skill in the art will readily recognize, network 400 canrepresent any type of overlay or software-defined network, such asNVGRE, STT, or even overlay technologies yet to be invented.

The VNIDs can represent the segregated virtual networks in overlaynetwork 400. Each of the overlay tunnels (VTEPs 408A-D) can include oneor more VNIDs. For example, VTEP 408A can include VNIDs 1 and 2, VTEP408B can include VNIDs 1 and 2, VTEP 408C can include VNIDs 1 and 2, andVTEP 408D can include VNIDs 1-3. As one of ordinary skill in the artwill readily recognize, any particular VTEP can, in other embodiments,have numerous VNIDs, including more than the 3 VNIDs illustrated in FIG.4.

The traffic in overlay network 400 can be segregated logically accordingto specific VNIDs. This way, traffic intended for VNID 1 can be accessedby devices residing in VNID 1, while other devices residing in otherVNIDs (e.g., VNIDs 2 and 3) can be prevented from accessing suchtraffic. In other words, devices or endpoints connected to specificVNIDs can communicate with other devices or endpoints connected to thesame specific VNIDs, while traffic from separate VNIDs can be isolatedto prevent devices or endpoints in other specific VNIDs from accessingtraffic in different VNIDs.

Servers 404A-D and VMs 404E-I can connect to their respective VNID orvirtual segment, and communicate with other servers or VMs residing inthe same VNID or virtual segment. For example, server 404A cancommunicate with server 404C and VMs 404E and 404G because they allreside in the same VNID, viz., VNID 1. Similarly, server 404B cancommunicate with VMs 404F and 404H because they all reside in VNID 2.VMs 404E-I can host virtual workloads, which can include applicationworkloads, resources, and services, for example. However, in some cases,servers 404A-D can similarly host virtual workloads through VMs hostedon the servers 404A-D. Moreover, each of the servers 404A-D and VMs404E-I can represent a single server or VM, but can also representmultiple servers or VMs, such as a cluster of servers or VMs.

VTEPs 408A-D can encapsulate packets directed at the various VNIDs 1-3in the overlay network 400 according to the specific overlay protocolimplemented, such as VXLAN, so traffic can be properly transmitted tothe correct VNID and recipient(s). Moreover, when a switch, router, orother network device receives a packet to be transmitted to a recipientin the overlay network 400, it can analyze a routing table, such as alookup table, to determine where such packet needs to be transmitted sothe traffic reaches the appropriate recipient. For example, if VTEP 408Areceives a packet from endpoint 404B that is intended for endpoint 404H,VTEP 408A can analyze a routing table that maps the intended endpoint,endpoint 404H, to a specific switch that is configured to handlecommunications intended for endpoint 404H. VTEP 408A might not initiallyknow, when it receives the packet from endpoint 404B, that such packetshould be transmitted to VTEP 408D in order to reach endpoint 404H.Accordingly, by analyzing the routing table, VTEP 408A can lookupendpoint 404H, which is the intended recipient, and determine that thepacket should be transmitted to VTEP 408D, as specified in the routingtable based on endpoint-to-switch mappings or bindings, so the packetcan be transmitted to, and received by, endpoint 404H as expected.

However, continuing with the previous example, in many instances, VTEP408A may analyze the routing table and fail to find any bindings ormappings associated with the intended recipient, e.g., endpoint 404H.Here, the routing table may not yet have learned routing informationregarding endpoint 404H. In this scenario, the VTEP 408A may likelybroadcast or multicast the packet to ensure the proper switch associatedwith endpoint 404H can receive the packet and further route it toendpoint 404H.

In some cases, the routing table can be dynamically and continuouslymodified by removing unnecessary or stale entries and adding new ornecessary entries, in order to maintain the routing table up-to-date,accurate, and efficient, while reducing or limiting the size of thetable.

As one of ordinary skill in the art will readily recognize, the examplesand technologies provided above are simply for clarity and explanationpurposes, and can include many additional concepts and variations.

Depending on the desired implementation in the network 400, a variety ofnetworking and messaging protocols may be used, including but notlimited to TCP/IP, open systems interconnection (OSI), file transferprotocol (FTP), universal plug and play (UpnP), network file system(NFS), common internet file system (CIFS), AppleTalk etc. As would beappreciated by those skilled in the art, the network 400 illustrated inFIG. 4 is used for purposes of explanation, a network system may beimplemented with many variations, as appropriate, in the configurationof network platform in accordance with various embodiments of thepresent disclosure.

FIG. 5 illustrates an example health checker 500 for managing a statemachine according to some aspects of the subject technology. The healthchecker 500 can be made up of one or more computing nodes in a computingnetwork. For example, the health checker 500 can be made up of one ormore switches, routers, end points, computing devices, etc., orcombination thereof in the computing network. The heath checker 500 andits components can reside in any computing device in the computingnetwork either separately or as whole unit.

The health checker 500 can be configured to monitor the health of astate machine and determine whether the state machine is in aninconsistent state. If the health checker 500 determines that a statemachine is in an inconsistent sate, the health checker 500 can cause thestate machine to change from the inconsistent state to a new state.

A state machine can be any of a plurality of network devices at thecomputing network and may be any device capable of receiving ortransmitting a packet at the computing network, such as an intermediatenetwork node (e.g., a router) and a switch. Each state of a statemachine can correspond to one or more specific actions that the statemachine can perform in the respective state. For example, when the statemachine is in an “initialization” state, only a specific action of“initialization” can be performed on the state machine. Other actionsthat are inconsistent with the “initialization” state may be prohibited.Further, in some embodiments, when a state machine is in a specificstate, the state machine can only transition to one or more particularstates such that transitions to other states can be prohibited.

To determine whether a state machine is in an inconsistent state, thehealth checker 500 can be configured to determine a current state of thestate machine and an anticipated sate of the state machine, anddetermine whether the current state and anticipated state areinconsistent with each other.

A current state of a state machine is the state that the state machineis currently in, whereas an anticipated state of the state machine is astate that the state machine should be in according to events that havehappened on the state machine and/or other factors. Software systems ona state machine may be event-driven, meaning that the state machine maycontinuously wait for an occurrence of a specific external or internalevent. Each state of the state machine can be a result of an occurrenceof a particular set of external or internal events.

An event can be any type of action, input, output, etc., received orperformed by the state machine. For example, past events on the statemachine may indicate that a message was sent by the state machine andthe state machine has been awaiting a reply. After an anticipated timeperiod, the reply should have arrived. The anticipated state should be astate that is consistent with the reply having arrived rather thanwaiting for the reply.

Health checker 500 can include an analysis module 502 configured todetermine whether a state machine is in an inconsistent state. Forexample, the analysis module 502 can determine the current andanticipated state of the state machine to determine whether the statemachine is in an inconsistent state. In some embodiments, the analysismodule 502 can determine whether a state machine is in an inconsistentstate periodically, such as according to a predefined schedule. Asanother example, the analysis module 502 can determine whether a statemachine is in an inconsistent state in response to occurrence ofspecified events such as the state machine rebooting.

The analysis module 502 can determine the current state of a statemachine in numerous ways. For example, in some embodiments, the analysismodule 502 can query the state machine for the current state of thestate machine. As another example, the analysis module can analyze anactive log of the state machine to determine the current state of thestate machine. The active log can list events, either internal orexternal, that have occurred on or been performed by a particular statemachine, as well as include metadata describing the events, such as thetime that the events occurred. For example, the active log can includecheckpoints for continued operations or configuration events that haveoccurred on the particular state machine. The configuration events orany other event on the state machine may include external or internalevents such as a mouse click, a button press, a time tick, sending adata packet, arrival of a data packet, etc. Each state machine canmaintain an active log and the analysis module 502 can be configured toaccess the active log of a state machine to analyze the events anddetermine a current state of the state machine.

The analysis module 502 can determine the anticipated state of a statemachine in numerous ways. For example, in some embodiments, the analysismodule 502 can determine the anticipated state of a state machine usinga table of possible states of a state machine. The table can listpossible states of a state machine, events that can result in a specificstate of the state machine, actions that the state machine can performwhile in a specific, or all states that a specific state of the statemachine is allowed to transition to.

The health checker 500 can include a data storage 504 configured tomaintain the table. The analysis module 502 can communicate with thedata storage 504 to access the table to determine the anticipated stateof a state machine. The analysis module 502 can compare the events thathave occurred on the state machine to the table to determine theanticipated state of the state machine based on the events.

In some embodiments, the analysis module 502 may determine ananticipated state of a state machine using one or more machine-learningalgorithms based upon data stored in an active log of the state machine.For example, one or more machine-learning algorithms can be pre-trainedusing historical data stored in the active log of the state machine oractive logs of other state machines to determine the anticipated stateof the state machine.

In some embodiments, the analysis module 502 can determine ananticipated state of a state machine based upon states of other statemachines that the state machine has been in communication with. Forexample, if a state machine is waiting for a reply as a result of havingtransmitted a message to another state machine, the analysis module 502may query the other state machine to determine whether the other statemachine received the message and/or if a reply message has beentransmitted by the other state machine.

The analysis module 502 can compare the current state of the statemachine and the anticipated state of the state machine to determinewhether the state machine is in an inconsistent state. If the currentstate and the anticipated state match, the analysis module 502 candetermined that the state machine is not in an inconsistent state.Alternatively, if the current state and the anticipated state do notmatch, the analysis module 502 can determine that the state machine isin an inconsistent state.

The health checker 500 can include a state change module 506 configuredto cause a state machine in an inconsistent state to change from itscurrent inconsistent state to a new state. The state change module 506may send a command to the state machine that causes the state machine toperform a specific action or a set of actions resulting in the statemachine changing to the new state. For example, the specific actions mayinclude, but are not limited to, reverting the state machine to aprevious state that is immediately before the inconsistent state byrolling back changes made on the state machine and/or re-executing aprevious action executed by the state machine before the inconsistentstate (e.g., resend a message that requires a response), rebooting thestate machine, etc. In some embodiments, the state change module 506 maycause one or more processes in the computing network to be terminated tofree up resources for the state machine, thereby enabling the statemachine to transition from an inconsistent state.

The state change module 506 can determine a new state of a state machineand a suitable action to change a current state of the state machine byanalyzing the table of possible states on the state machine based atleast upon the current events on the state machine, an anticipated stateof the state machine, or the events that have taken place on the statemachine. For example, assuming that the present state of the statemachine is an “initialization” state and an anticipated state of thestate machine is a power-up state, the table may include two possibletransitions that can be performed on the state machine to transfer fromthe “initialization” to two possible subsequent states (e.g., “shutdown” or “power up”). The state change module 506 may determine asuitable action, such as “power up,” to change the current state (i.e.,“initialization”) of the state machine to a new state, a “power upstate.”

In some embodiments, the state change module 506 may use one or moremachine learning algorithms to analyze past events that have takenplace, current events and/or network resources (e.g., network bandwidthand processing capacity) to determine a new state for the state machineand a suitable action to change a current state of the state machine.For example, a new state may be a previous state immediately before theinconsistent state. The state change module 506 can retrieve theprevious action performed by the state machine from the correspondingactive log of the state machine and transmit a command causing the statemachine to re-execute the previous command.

Subsequent to sending the command to the state machine and causing thestate machine to change from the current state, the state change module506 may communicate with the analysis module 502 to determine whether aconsistent state has been reached on the state machine. In an event thatthe state machine is still in the inconsistent state after apredetermined time period, the state change module 506 may cause asecondary action to be performed. For example, the state change module506 may cause the state machine to be powered down or send an alertmessage to an administrator of the state machine.

Having disclosed some basic system components and concepts, thedisclosure now turns to the example method shown in FIG. 6. For the sakeof clarity, the method is described in terms of systems 110, 200, 250,300, 400 and 500, as shown in FIGS. 1-5, configured to practice themethod. The steps outlined herein are example and can be implemented inany combination thereof, including combinations that exclude, add, ormodify certain steps.

FIG. 6 illustrates an example process 600 of managing states of a statemachine in a computing network in accordance with variousimplementations. It should be understood that there can be additional,fewer, or alternative steps performed in similar or alternative orders,or in parallel, within the scope of the various embodiments unlessotherwise stated. The example method 600 begins at step 610 with ahealth checker 500 determining a current state of a state machine. Thehealth checker 500 can periodically determine the current state of thestate machine according to a predefined schedule or in response tocertain events happening on the state machine. The health checker 500can determine the current state of the state machine by querying thestate machine, analyzing an active log of the state machine, etc.

At step 620, the health checker 500 can further determine an anticipatedstate of the state machine. The health checker 500 can determine theanticipated state by analyzing an active log of the state machine orstate information of state machines that the state machine has been incommunication with, analyzing a table of possible states on the statemachine, using one or more machine-learning algorithms, etc.

At step 630, the health checker 500 can determine whether the statemachine is in an inconsistent. For example, the health checker 500 cancompare the current state of the state machine to an anticipated stateof the state machine to determine whether the state machine is in aninconsistent state.

If at step 620 the health checker 500 determines that the state machineis in an inconsistent state, (e.g., the current state does not match theanticipated state), the method can continue to step 640 where the healthchecker 500 can determine a suitable action to change the current stateof the state machine. The suitable action may include, but is notlimited to, reverting the state machine to a previous state that isimmediately before the inconsistent state by rolling back changes madeon the state machine, and re-execute a previous action executed by thestate machine before the inconsistent state (e.g., resend a message thatrequires a response). In some embodiments, a suitable action may berebooting the state machine or causing one or more processes in thecomputing network to be terminated to free up resources for the statemachine.

At step 650, the health checker can cause the one or suitable actions tobe performed by the state machine. For example, the health checker cantransmit a command to the state machine or one or more other statemachines that have communicated with the state machine to cause thereceiving state machine to perform a specified action. The specifiedaction can cause the state machine to change from the inconsistent stateto a new state.

As one of ordinary skill in the art will readily recognize, the examplesand technologies provided above are simply for clarity and explanationpurposes, and can include many additional concepts and variations.

For clarity of explanation, in some instances the present technology maybe presented as including individual functional blocks includingfunctional blocks comprising devices, device components, steps orroutines in a method embodied in software, or combinations of hardwareand software.

In some embodiments the computer-readable storage devices, mediums, andmemories can include a cable or wireless signal containing a bit streamand the like. However, when mentioned, non-transitory computer-readablestorage media expressly exclude media such as energy, carrier signals,electromagnetic waves, and signals per se.

Methods according to the above-described examples can be implementedusing computer-executable instructions that are stored or otherwiseavailable from computer readable media. Such instructions can comprise,for example, instructions and data which cause or otherwise configure ageneral purpose computer, special purpose computer, or special purposeprocessing device to perform a certain function or group of functions.Portions of computer resources used can be accessible over a network.The computer executable instructions may be, for example, binaries,intermediate format instructions such as assembly language, firmware, orsource code. Examples of computer-readable media that may be used tostore instructions, information used, and/or information created duringmethods according to described examples include magnetic or opticaldisks, flash memory, USB devices provided with non-volatile memory,networked storage devices, and so on.

Devices implementing methods according to these disclosures can comprisehardware, firmware and/or software, and can take any of a variety ofform factors. Typical examples of such form factors include laptops,smart phones, small form factor personal computers, personal digitalassistants, rackmount devices, standalone devices, and so on.Functionality described herein also can be embodied in peripherals oradd-in cards. Such functionality can also be implemented on a circuitboard among different chips or different processes executing in a singledevice, by way of further example.

The instructions, media for conveying such instructions, computingresources for executing them, and other structures for supporting suchcomputing resources are means for providing the functions described inthese disclosures.

Although a variety of examples and other information was used to explainaspects within the scope of the appended claims, no limitation of theclaims should be implied based on particular features or arrangements insuch examples, as one of ordinary skill would be able to use theseexamples to derive a wide variety of implementations. Further andalthough some subject matter may have been described in languagespecific to examples of structural features and/or method steps, it isto be understood that the subject matter defined in the appended claimsis not necessarily limited to these described features or acts. Forexample, such functionality can be distributed differently or performedin components other than those identified herein. Rather, the describedfeatures and steps are disclosed as examples of components of systemsand methods within the scope of the appended claims. Moreover, claimlanguage reciting “at least one of” a set indicates that one member ofthe set or multiple members of the set satisfy the claim.

For clarity of explanation, in some instances the present technology maybe presented as including individual functional blocks includingfunctional blocks comprising devices, device components, steps orroutines in a method embodied in software, or combinations of hardwareand software.

Note that in certain example implementations, the optimization and/orplacement functions outlined herein may be implemented by logic encodedin one or more tangible, non-transitory media (e.g., embedded logicprovided in an application specific integrated circuit [ASIC], digitalsignal processor [DSP] instructions, software [potentially inclusive ofobject code and source code] to be executed by a processor, or othersimilar machine, etc.). The computer-readable storage devices, mediums,and memories can include a cable or wireless signal containing a bitstream and the like. However, when mentioned, non-transitorycomputer-readable storage media expressly exclude media such as energy,carrier signals, electromagnetic waves, and signals per se.

Methods according to the above-described examples can be implementedusing computer-executable instructions that are stored or otherwiseavailable from computer readable media. Such instructions can comprise,for example, instructions and data which cause or otherwise configure ageneral purpose computer, special purpose computer, or special purposeprocessing device to perform a certain function or group of functions.Portions of computer resources used can be accessible over a network.The computer executable instructions may be, for example, binaries,intermediate format instructions such as assembly language, firmware, orsource code. Examples of computer-readable media that may be used tostore instructions, information used, and/or information created duringmethods according to described examples include magnetic or opticaldisks, flash memory, USB devices provided with non-volatile memory,networked storage devices, and so on.

Devices implementing methods according to these disclosures can comprisehardware, firmware and/or software, and can take any of a variety ofform factors. Typical examples of such form factors include laptops,smart phones, small form factor personal computers, personal digitalassistants, and so on. Functionality described herein also can beembodied in peripherals or add-in cards. Such functionality can also beimplemented on a circuit board among different chips or differentprocesses executing in a single device, by way of further example.

The instructions, media for conveying such instructions, computingresources for executing them, and other structures for supporting suchcomputing resources are means for providing the functions described inthese disclosures.

Although a variety of examples and other information was used to explainaspects within the scope of the appended claims, no limitation of theclaims should be implied based on particular features or arrangements insuch examples, as one of ordinary skill would be able to use theseexamples to derive a wide variety of implementations. Further andalthough some subject matter may have been described in languagespecific to examples of structural features and/or method steps, it isto be understood that the subject matter defined in the appended claimsis not necessarily limited to these described features or acts. Forexample, such functionality can be distributed differently or performedin components other than those identified herein. Rather, the describedfeatures and steps are disclosed as examples of components of systemsand methods within the scope of the appended claims.

We claim:
 1. A computer-implemented method, comprising: determining acurrent state of a state machine in a computing network; determining ananticipated state of the state machine; determining whether the statemachine is in an inconsistent state by comparing the current state andthe anticipated state of the state machine; determining a specificaction to change the current state of the state machine; and causing thespecific action to be taken to switch the current state of the statemachine.
 2. The computer-implemented method of claim 1, wherein thecurrent state of the state machine is determined by analyzing an activelog of the state machine.
 3. The computer-implemented method of claim 1,wherein the anticipated state is determined by analyzing an active logof the state machine or state information of state machines that thestate machine has been in communication with, analyzing a table ofpossible states on the state machine, or using one or moremachine-learning algorithms.
 4. The computer-implemented method of claim1, wherein the action includes at least one of rebooting the statemachine or causing one or more processes in the computing network to beterminated to free up resources for the state machine.
 5. Thecomputer-implemented method of claim 1, further comprising: in responseto the state machine being in the inconsistent state, determining aprevious state of the state machine that is immediately before thecurrent state by looking up a table of possible states on the statemachine, the table including one or more actions that the state machineis allowed to perform under the specific state and all possible statesthat the previous state is allowed to transition to.
 6. Thecomputer-implemented method of claim 5, further comprising: causing thestate machine to be reverted to the previous state; and causing one ormore actions associated with the previous state of the state machine tobe re-executed.
 7. The computer-implemented method of claim 5, furthercomprising: determining that an old state is removed from the statemachine or a new state is added to the state machine; and updating oneor more entries of the table associated with the old state or the newstate.
 8. The computer-implemented method of claim 1, wherein thecurrent state of the state machine is determined periodically accordingto a predefined schedule or in response to at least one particular eventhappening on the state machine.
 9. A system, comprising: at least oneprocessor; and memory including instructions that, when executed by theat least one processor, cause the system to: determine a current stateof a state machine in a computing network; determine an anticipatedstate of the state machine; determine whether the state machine is in aninconsistent state by comparing the current state and the anticipatedstate of the state machine; determine a specific action to change thecurrent state of the state machine; and cause the specific action to betaken to switch the current state of the state machine.
 10. The systemof claim 9, wherein the current state of the state machine is determinedby analyzing an active log of the state machine.
 11. The system of claim9, wherein the anticipated state is determined by analyzing an activelog of the state machine or state information of state machines that thestate machine has been in communication with, analyzing a table ofpossible states on the state machine, or using one or moremachine-learning algorithms.
 12. The system of claim 9, wherein theaction includes at least one of rebooting the state machine or causingone or more processes in the computing network to be terminated to freeup resources for the state machine.
 13. The system of claim 9, whereinthe instructions when executed further cause the system to: in responseto the state machine being in the inconsistent state, determine aprevious state of the state machine that is immediately before thecurrent state by looking up a table of possible states on the statemachine, the table including one or more actions that the state machineis allowed to perform under the specific state and all possible statesthat the previous state is allowed to transition to.
 14. The system ofclaim 13, wherein the instructions when executed further cause thesystem to: cause the state machine to be reverted to the previous state;and cause one or more actions associated with the previous state of thestate machine to be re-executed.
 15. The system of claim 13, wherein theinstructions when executed further cause the system to: determine thatan old state is removed from the state machine or a new state is addedto the state machine; and update one or more entries of the tableassociated with the old state or the new state.
 16. The system of claim9, wherein the current state of the state machine is determinedperiodically according to a predefined schedule or in response to atleast one particular event happening on the state machine.
 17. Anon-transitory computer-readable storage medium including instructionsthat, when executed by at least one processor of a computing system,cause the computing system to: determine a current state of a statemachine in a computing network; determine an anticipated state of thestate machine; determine whether the state machine is in an inconsistentstate by comparing the current state and the anticipated state of thestate machine; determine a specific action to change the current stateof the state machine; and cause the specific action to be taken toswitch the current state of the state machine.
 18. The non-transitorycomputer-readable storage medium of claim 17, wherein the instructions,when executed by the at least one processor of the computing system,further cause the computing system to: in response to the state machinebeing in the inconsistent state, determine a previous state of the statemachine that is immediately before the current state by looking up atable of possible states on the state machine, the table including oneor more actions that the state machine is allowed to perform under thespecific state and all possible states that the previous state isallowed to transition to.
 19. The non-transitory computer-readablestorage medium of claim 18, wherein the instructions, when executed bythe at least one processor of the computing system, further cause thecomputing system to: cause the state machine to be reverted to theprevious state; and cause one or more actions associated with theprevious state of the state machine to be re-executed.
 20. Thenon-transitory computer-readable storage medium of claim 18, wherein theinstructions, when executed by the at least one processor of thecomputing system, further cause the computing system to: determine thatan old state is removed from the state machine or a new state is addedto the state machine; and update one or more entries of the tableassociated with the old state or the new state.